Llama-3.2-90B-Vision-Instruct vs Llama-3.1-70B-Instruct
Llama-3.2-90B-Vision-Instruct comes out ahead, 44 to 39 on our weighted score.
- Our pick
Meta
Llama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
Meta
Llama-3.1-70B-Instruct
39/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
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Llama-3.2-90B-Vision-Instruct is our pick
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Llama-3.1-70B-Instruct (39). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityLlama-3.1-70B-InstructCapabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 · Llama-3.2-90B-Vision-Instruct 125.5
- Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextAbout the sameLlama-3.2-90B-Vision-Instruct 128,000 · Llama-3.1-70B-Instruct 128,000 tokens
- Widest inputsLlama-3.2-90B-Vision-InstructLlama-3.2-90B-Vision-Instruct: Text, Images · Llama-3.1-70B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.2-90B-Vision-Instruct | Llama-3.1-70B-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 46 | 47 |
| Inputs & features | 20% | 50 | 25 |
| Context window | 13% | 24 | 24 |
| Overall | 100% | 44/100 | 39/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 125.5 | 125.9 (best) |
| ECI rank | #150 of 165 | #149 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 41.0% | 44.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.6% | 3.6% (best) |
| Price per million tokens | ||
| Input | — | $0.72 |
| Output | — | $0.72 |
| Cached input | — | — |
| Blended (3:1) | — | $0.72 |
| Long-context rate | — | Same rate |
| Price source | — | Median of 8 providers |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 4,096 tokens | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenLlama 3.2 Community License | Open |
| API model ID | — | — |
| API providers | 1 | 8 (best) |
| Released | Sep 25, 2024 | Jul 23, 2024 |
| Knowledge cutoff | Dec 2023 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Llama-3.2-90B-Vision-Instruct—
Llama-3.1-70B-Instruct$8.64
Which should you choose?
Which is better: Llama-3.2-90B-Vision-Instruct or Llama-3.1-70B-Instruct?
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Llama-3.1-70B-Instruct (39). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Llama-3.2-90B-Vision-Instruct or Llama-3.1-70B-Instruct?
Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 8 API providers). . At a typical mix of three input tokens to one output token, that is $0.72 per million tokens for Llama-3.1-70B-Instruct versus . Llama-3.2-90B-Vision-Instruct has no published per-token price.
Which scores higher on benchmarks?
Llama-3.1-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 (#149 of 165) and Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165). The confidence ranges of the top two overlap (120.8–128.2 vs 120.3–127.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Llama-3.2-90B-Vision-Instruct 41.0%; OTIS Mock AIME 2024–2025 — Llama-3.1-70B-Instruct 3.6%, Llama-3.2-90B-Vision-Instruct 2.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct and Llama-3.1-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.1-70B-Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Llama-3.2-90B-Vision-Instruct and Llama-3.1-70B-Instruct share the same 128,000-token context window. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Llama-3.1-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-90B-Vision-Instruct accepts text and images; Llama-3.1-70B-Instruct accepts text. Llama-3.2-90B-Vision-Instruct handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Llama-3.2-90B-Vision-Instruct is the newest, released Sep 25, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Llama-3.1-70B-Instruct Dec 2023.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.